• Beyond using composite measures to analyze the effect of unmet supportive care needs on caregivers’ anxiety and depression

      Lambert, Sylvie D.; Hulbert-Williams, Nicholas J.; Belzile, Eric; Ciampi, Antonio; Girgis, Afaf; McGill University; University of Chester; University of New South Wales (Wiley, 2018-03-06)
      Objective: Caregiver research has relied on composite measures (e.g., count) of unmet supportive care needs to determine relationships with anxiety and depression. Such composite measures assume that all unmet needs have a similar impact on outcomes. The purpose of this study is to identify individual unmet needs most associated with caregivers’ anxiety and depression. Methods: 219 Caregivers completed the 44-item Supportive Care Needs Survey and the Hospital Anxiety and Depression scale [minimal clinically important difference (MCID)=1.5] at 6-8 months, 1, 2, 3.5, and 5 years following the patients' cancer diagnosis. The list of needs was reduced using Partial Least Square regression and those with a Variance Importance in Projection > 1 were analyzed using Bayesian Model Averaging. Results: Across time, eight items remained in the top 10 based on prevalence and were labelled “core”. Three additional ones were labelled “frequent”, as they remained in the top 10 from 1- year onwards. Bayesian Model Averaging identified a maximum of four significant unmet needs per time point – all leading to a difference greater than the MCID. For depression, none of the core unmet needs were significant, rather significance was noted for frequent needs and needs that were not prevalent. For anxiety, 3/8 core and 3/3 frequent unmet needs were significant. Conclusions: Prevalent Those unmet needs that are most prevalent are not necessarily the most significant ones, and findings provide an evidence-based framework to guide the development of caregiver interventions. A broader contribution is proposing a different approach to identify significant unmet needs.
    • Relationships between unmet needs, depression and anxiety in non-advanced cancer patients

      Ferrari, Martina; Ripamonti, Carla I; Hulbert-Williams, Nicholas J.; Miccinesi, Guido; University of Chester; Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy; ISPO Clinical Epidemiology Unit, Florence, Italy (Wichtig Publishing, 2018-04-16)
      Introduction: In oncology settings, less attention is given to patients’ unmet need and to existential and emotional distress, compared to physical symptoms. We aimed to evaluate correlations between unmet needs and emotional distress (self-reported anxiety and depression) in a consecutive cohort of cancer patients. The influence of socio- demographic and clinical factors was also considered. Methods: Three hundred cancer patients recruited from an out-patient Supportive Care Unit of a Comprehensive Cancer Centre completed the Need Evaluation Questionnaire (NEQ) and the Edmonton Symptom Assessment System (ESAS). Unmet needs covered five distinct domains (informational, care/assistance, relational, psycho-emotional and material). Results: After removal of missing data, we analysed data from 258 patients. Need for better information on future health concerns (42%), better services from the hospital (43%), and to speak with individuals in the same condition (31%) were the most frequently reported as unmet. Based on the ESAS, 27.2% and 17.5% of patients respectively had a score of anxiety or depression > 3 and needed further examination for psychological distress. Female patients had significantly higher scores for anxiety (p<.001) and depression (p=.008) compared to males. Unmet needs were significantly correlated with both anxiety (rs=.283) and depression (rs=.284). Previous referral to a psychologist was significantly associated with depression scores (p=.015). Results were confirmed by multiple regression analysis. Conclusions: Screening for unmet needs whilst also considering socio-demographic and clinical factors, allows early identification of cancer patients with emotional distress. Doing so will enable optimal management of psychological patient-reported outcomes in oncology settings.